CN115290655B - Imaging method of defect detection photo-thermal fusion imaging device based on heat flow diffusion tracking - Google Patents
Imaging method of defect detection photo-thermal fusion imaging device based on heat flow diffusion tracking Download PDFInfo
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Abstract
The invention provides a defect accurate detection photo-thermal fusion imaging device and method based on heat flow diffusion tracking. The invention provides a discrete cosine-Rucaskarad method based on thermal wave time-frequency characteristics, which is used for accurately tracking the time-frequency domain change process of the thermal wave characteristics and constructing the plane size of a defect by adopting a reverse reconstruction method. Finally, the defect size detection error of the composite material, the metal material and the like is less than 2.5 percent.
Description
Technical Field
The invention belongs to the technical fields of photothermal science and detection technology, signal analysis and feature extraction, image processing and identification, and particularly relates to a device and a method for precisely detecting photo-thermal fusion imaging based on heat flow diffusion tracking. The imaging device and the imaging method are suitable for the fields of precise nondestructive detection and evaluation of defects/damages of materials such as aerospace, microelectronics, micro-nano structures and the like.
Background
As an emerging nondestructive testing technology, the infrared thermal wave imaging testing technology has the advantages of non-contact, intuitiveness, large detection area and the like, and is suitable for nondestructive testing, quality evaluation and the like of thin metal components, composite material components and high polymer materials. The infrared thermal wave imaging detection technology adopts an external excitation source to carry out active thermal excitation loading on a detected test piece, heat flow permeates from the surface of the detected test piece to the inside, and when defects exist in the detected test piece, the defects are obviously different from the detected test piece material in the thermal physical parameters, so that the heat flow diffusion process is accelerated or hindered. At the moment, the blocking effect of the defects is diffused to the surface of the detected test piece through heat conduction, and the infrared radiation difference of the detected test piece can be identified by utilizing the thermal infrared imager, so that the effective identification of the defects is realized. The propagation of the heat flow completely depends on the temperature gradient in the detected test piece, and the heat flow diffuses from a high-temperature area to a low-temperature area, so that the amplification detection effect on the defects exists, and the transverse heat diffusion of the heat flow inevitably leads to the defect that the detected size is larger than the actual size. Although the thermal wave imaging detection method can realize the amplification detection of small-scale defects by using a non-uniform diffusion detection means of heat flow, the defect size detection deviation is large, so that the accurate defect detection based on the infrared thermal wave imaging detection technology faces a great challenge, and if the transverse thermal diffusion effect of the heat flow is effectively inhibited in the defect detection process, the defect detection method becomes a key technical bottleneck for realizing the accurate defect detection.
In the prior art, wei Jiacheng, guizhou university, et al, proposed a similar optical flow method (Likeness optical flow, LOF) that can estimate the thermal flow gradient diffusion field in two-dimensional corresponding thermal signature images and utilize the method to reduce the impact of lateral thermal diffusion on detection accuracy. Simulation and experiments prove that the LOF method plays a good role in inhibiting the transverse heat spreading effect of the heat flow of the infrared image sequence, and meanwhile, the method has a good characteristic enhancement effect for a specific characteristic extraction method, but in the LOF iterative operation process, strict criteria are not formulated for the selection of an initial image and a termination image, so that the accuracy of an obtained result is not significant when the defect scale is unknown. The LOF method is optimized by Harbin university of industry Wang Fei and the like, a global smooth assumption is added on the basis of an optical flow basic constraint equation based on a Horn-Schink algorithm with gradient change, the completeness of the equation is realized, defect characteristics are extracted through a characteristic extraction algorithm, defect depth information is obtained through theoretical calculation, the depth information is fed back to a characteristic image iteration model, and finally effective suppression of the defects on transverse heat diffusion is realized. However, since the Horn-Schuk algorithm is applied on the premise that the image moves slowly (i.e. the heat flow spreads slowly), the defect equivalent diameter accuracy still has a large deviation from the actual defect diameter. In the method, in order to realize accurate measurement of the debonding defect of the thermal barrier coating structure, the femtosecond laser is adopted to carry out active thermal excitation loading on a test piece, so that the transverse thermal diffusion time of heat flow is shortened, and the accurate measurement of the defect size is realized, but the method also brings the problem of low signal-to-noise ratio of defect detection, and can not be recognized for smaller debonding defects. The university of capital and university of Bejing and Feng Lichun and the like (patent number ZL200510077750. X) of New technology Co., ltd.) propose a method for reconstructing an infrared thermal wave detection tomographic image, in which three-dimensional reconstruction of defects is realized only according to a theoretical formula of diffusion characteristics of heat flow in the depth direction, and the planar diffusion amplification effect of the heat flow is not considered, so that the obtained tomographic image is pseudo-tomographic image only in the depth direction, and the obtained equivalent diameter of the defects has larger deviation from the actual diameter. In summary, the current research on infrared thermal wave imaging detection methods mainly focuses on how to three-dimensionally locate defects, and because of the specificity of heat flow gradient diffusion, there is a great challenge to precisely quantitatively characterize the sizes of defects, so that the research on the aspect is generally less.
In order to fully consider the heat flow gradient diffusion characteristic and further accurately quantify and characterize the defect size, the invention relates to a defect accurate detection photo-thermal fusion imaging device and method based on heat flow diffusion tracking.
Disclosure of Invention
The invention aims to solve the problems in the prior art and provides a photo-thermal fusion imaging device and a photo-thermal fusion imaging method for accurately detecting defects based on heat flow diffusion tracking. The invention is suitable for nondestructive testing of composite materials, metal materials and the like in the fields of aerospace, microelectronics, micro-nano structures and the like.
The invention is realized by the following technical scheme that the invention provides a defect accurate detection photo-thermal fusion imaging device based on heat flow diffusion tracking, which comprises a thermal infrared imager, a first BNC control line, a second BNC control line, a first Ethernet line, a conducting optical fiber, an air-cooling refrigerator, a semiconductor refrigerator, a laser, a control line, a laser power supply, a third BNC control line, a function generator, a first USB communication line, a fourth BNC control line, a lock-in amplifier, a fifth BNC control line, a data acquisition card, a second Ethernet line, an optical camera, a computer, a second USB communication line, a motion controller, a motion control line, a two-dimensional mobile station, a cylindrical lens, a first polarizer, an engineering diffuser, a sleeve, a collimating mirror, a clamp, a test piece and a second polarizer;
the computer is provided with four signal ends, one signal input end of the computer is connected with the signal output end of the thermal infrared imager through a first Ethernet wire, the second signal input end of the computer is connected with the signal output end of the optical camera through a second Ethernet wire, the third signal output end of the computer is connected with the input end of the function generator through a first USB communication wire, the fourth signal output end of the computer is connected with the input end of the motion controller through a second USB communication wire, one signal input end of the thermal infrared imager is connected with the output end of the function generator through a first BNC control wire, the second signal output end of the thermal infrared imager is connected with the input end of the data acquisition card through a second BNC control wire, the air cooling refrigerator, the semiconductor refrigerator and the laser are mechanically connected with the collimating mirror through a conducting optical fiber, the signal output end of the laser is connected with the collimating mirror through a cylindrical lens, the first polarizer, the engineering body, the sleeve and the collimating mirror through threads are connected on the sleeve, the signal output end of the laser power supply is connected with the input end of the laser through a control wire, the signal output end of the laser power supply is connected with the input end of the motion controller through the BNC control wire, the signal output end of the laser power supply is connected with the output end of the thermal infrared imager through the second BNC control wire, the signal output end of the thermal infrared imager is connected with the optical fiber through the output end of the motion controller through the second BNC control wire, the signal output end of the thermal infrared imager is connected with the optical fiber is connected with the output end of the optical fiber through the optical fiber.
The invention provides an imaging method for precisely detecting defects of a photo-thermal fusion imaging device based on heat flow diffusion tracking, which specifically comprises the following steps:
step one: defining a test piece to be detected, and placing the test piece on a two-dimensional mobile station;
step two: starting a defect accurate detection photo-thermal fusion imaging device based on heat flow diffusion tracking;
step three: after the laser power supply is turned on for a plurality of minutes, the laser, the air cooling refrigerator and the semiconductor refrigerator already control the temperature of the laser to be at a preset temperature, and the laser is turned on at the moment;
step four: starting the thermal infrared imager and the optical camera, imaging the test sample in real time, irradiating the test sample by using the laser, controlling the motion controller by the computer, and further adjusting the two-dimensional moving table to ensure that the laser beam irradiation positions are all in the fields of view of the thermal infrared imager and the optical camera;
step five: the computer controls the function generator to generate a pulse trigger signal, one path of the pulse trigger signal controls the laser to generate constant pulse laser with fixed power, the other path of the pulse trigger signal controls the infrared thermal imager to acquire a thermal radiation image of a test piece according to fixed frequency, meanwhile, the computer controls the two-dimensional moving table and the optical camera to work, the moving direction of the two-dimensional moving table is perpendicular to the direction of the line laser, the positions of the infrared thermal imager, the laser and the optical camera are relatively static, the test piece moves at a uniform speed along with a certain direction of the two-dimensional moving table, the position of the line scanning laser acting on a test field is fixed, and image sequence reconstruction is carried out after scanning is completed;
step six: the reconstructed image sequence is equivalent to the thermal image response stimulated by the pulse heat source, and the reconstructed image is subjected to discrete cosine change to obtain the characteristic response image sequence;
step seven: characteristic image sequences of different frequency components can be obtained through discrete cosine transformation, and a corresponding relation curve of phase characteristic differences of the defect position and the defect-free position of the test piece and different frequencies is selected at the moment;
step eight: based on two characteristic images, the motion velocity v of the image along the x and y directions is obtained by adopting the method of Rucaskaner x ,v y ；
Step nine: acquiring a final characteristic image;
step ten: registering and fusing the acquired characteristic image and the image acquired by the optical camera, and acquiring a characteristic value between pixel gaps of the original infrared characteristic image by adopting a fitting method;
step eleven: based on the obtained photo-thermal fusion imaging detection result, performing binarization threshold segmentation and connected domain marking to realize accurate defect detection;
step twelve: after the test is finished, 5 minutes later, the laser power supply, the laser, the function generator, the data acquisition card, the lock-in amplifier, the optical camera and the thermal infrared imager are turned off.
Further, in step two, the computer, the laser power supply, the data acquisition card, the function generator and the lock-in amplifier are turned on.
Further, in step three, the laser power was turned on for 2 minutes and the laser temperature was controlled at 15 ℃.
Further, in the fourth step, the polarization direction of the polarizer arranged at the front end of the laser is consistent with that of the polarizer in front of the thermal infrared imager, so that effective filtering of signals is achieved, the engineering diffuser arranged at the front end of the laser converts a Gaussian light source into uniform light, and the cylindrical lens converts the uniform light source into a linear laser light source.
Further, in the fifth step, the Pixel of Δpixel_x column of the line laser heat source in the field of view perpendicular to the moving direction thereof is taken, and defined as the number of collected pixels for reconstruction, and during the scanning process, the Pixel of Δpixel_x column will sweep the surface of the detected object along with the heat source and collect and record according to a certain frequency, and in order to enable the Pixel of Δpixel_x column to record the heat wave signal of the whole sweeping range, the following relation needs to be satisfied:
wherein v is the moving speed of the two-dimensional mobile station, PL is the actual physical position corresponding to a single pixel, and f is the acquisition frequency of the thermal infrared imager;
after the line laser completely scans the tested test piece, the image sequence is reconstructed by using the following formula,
wherein T is seqi The method is characterized in that an ith frame image acquired by a thermal infrared imager is T seq1 1 The reconstructed first image.
Further, in the sixth step, the discrete cosine transform after reconstructing the image is specifically:
wherein C is u [T seq (t n )]The discrete cosine transform after reconstructing the image, a (u) is an orthogonal transform coefficient, and N is the number of reconstructed image frames.
Further, in step seven, the phase characteristic difference is defined as,
DiPH＝|Ph Nondefect {C u [T seq (t n )]}-Ph Defect {C u [T seq (t n )]}| (4)
wherein DipH is the difference in phase characteristics, ph Nondefect Mean value of phase characteristics of defect-free position, ph Defect The phase characteristic mean value of the defect position; selecting the phase characteristic images of the frequencies corresponding to the DipH peak position and the 1/2 position as P respectively peak And P peak/2 。
Further, in step eight, the rate of change of the two directions is obtained:
further, the finally acquired feature image is:
Ph＝Ph peak/2 -Ph peak ·v x -Ph peak ·v y (6)。
the beneficial effects of the invention are as follows:
(1) The invention discloses a heat flow diffusion tracking-based photo-thermal fusion imaging method for accurately detecting defects, and provides a discrete cosine-Rucaskard method based on heat wave time-frequency characteristics. Finally, the defect size detection error is less than 2.5%.
(2) The invention provides a multi-source multi-sensing data fusion imaging detection method based on an infrared thermal imager and a monocular optical camera, which is used for carrying out high-precision fusion on a characteristic image and an optical image obtained based on infrared thermal wave imaging, so that the defect detection resolution of an infrared thermal wave imaging detection technology can be improved, and finally, the defect positioning precision error is less than 0.1%.
(3) The invention discloses a defect accurate detection photo-thermal fusion imaging device based on heat flow diffusion tracking, which adopts a lock-in amplifier to monitor real-time synchronization of heat flow modulation signals and infrared thermal imager acquisition signals, and feeds back synchronization delay information to a function generator to realize accurate control of the signals.
Drawings
FIG. 1 is a line laser scanning schematic;
FIG. 2 is a photo-thermal fusion imaging device for accurately detecting defects based on heat flow diffusion tracking;
FIG. 3 is a schematic diagram of the detection result.
In the figure: the infrared imaging system comprises a 1-infrared thermal imager, a 2-first BNC control wire, a 3-second BNC control wire, a 4-first Ethernet wire, a 5-conducting optical fiber, a 6-air cooling refrigerator, a 7-semiconductor refrigerator, an 8-laser, a 9-control wire, a 10-laser power supply, a 11-third BNC control wire, a 12-function generator, a 13-first USB communication wire, a 14-fourth BNC control wire, a 15-lock-in amplifier, a 16-fifth BNC control wire, a 17-data acquisition card, a 18-second Ethernet wire, a 19-optical camera, a 20-computer, a 21-second USB communication wire, a 22-motion controller, a 23-motion control wire, a 24-two-dimensional moving table, a 25-cylindrical lens, a 26-first polarizer, a 27-engineering diffuser, a 28-sleeve, a 29-collimating mirror, a 30-clamp, a 31-test piece and a 32-second polarizer.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The invention aims to provide a defect accurate detection photo-thermal fusion imaging method based on heat flow diffusion tracking, which aims to solve the problem of low defect detection precision caused by heat flow transverse heat diffusion in the current infrared heat wave imaging detection process. Finally, the defect size detection error of the composite material, the metal material and the like is less than 2.5 percent.
The invention provides a multi-source multi-sensor fusion imaging detection method based on a thermal infrared imager and a monocular optical camera, which aims to solve the problem of lower defect position positioning precision in the detection process by simply relying on the thermal infrared imager at present. At present, the pixels of the thermal infrared imager are generally lower (640 x 512 pixels are the common thermal infrared imager), the resolution of the optical camera is generally higher, and the characteristic image and the optical image acquired based on the thermal infrared imaging are fused with high precision, so that the defect detection resolution of the thermal infrared imaging detection technology can be improved, and finally, the defect positioning precision error of a composite material, a metal material and the like can be less than 0.1%.
Referring to fig. 1-3, the invention provides a defect accurate detection photo-thermal fusion imaging device based on heat flow diffusion tracking, which comprises a thermal infrared imager, a first BNC control line, a second BNC control line, a first ethernet line, a conducting optical fiber, an air-cooled refrigerator, a semiconductor refrigerator, a laser, a control line, a laser power supply, a third BNC control line, a function generator, a first USB communication line, a fourth BNC control line, a lock-in amplifier, a fifth BNC control line, a data acquisition card, a second ethernet line, an optical camera, a computer, a second USB communication line, a motion controller, a motion control line, a two-dimensional mobile station, a cylindrical lens, a first polarizer, an engineering diffuser, a sleeve, a collimating mirror, a clamp, a test piece and a second polarizer;
the computer is provided with four signal ends, one signal input end of the computer is connected with the signal output end of the thermal infrared imager through a first Ethernet wire, the second signal input end of the computer is connected with the signal output end of the optical camera through a second Ethernet wire, the third signal output end of the computer is connected with the input end of the function generator through a first USB communication wire, the fourth signal output end of the computer is connected with the input end of the motion controller through a second USB communication wire, one signal input end of the thermal infrared imager is connected with the output end of the function generator through a first BNC control wire, the second signal output end of the thermal infrared imager is connected with the input end of the data acquisition card through a second BNC control wire, the air cooling refrigerator, the semiconductor refrigerator and the laser are mechanically connected with the collimating mirror through a conducting optical fiber, the signal output end of the laser is connected with the collimating mirror through a cylindrical lens, the first polarizer, the engineering body, the sleeve and the collimating mirror through threads are connected on the sleeve, the signal output end of the laser power supply is connected with the input end of the laser through a control wire, the signal output end of the laser power supply is connected with the input end of the motion controller through the BNC control wire, the signal output end of the laser power supply is connected with the output end of the thermal infrared imager through the second BNC control wire, the signal output end of the thermal infrared imager is connected with the optical fiber through the output end of the motion controller through the second BNC control wire, the signal output end of the thermal infrared imager is connected with the optical fiber is connected with the output end of the optical fiber through the optical fiber.
The invention provides an imaging method for precisely detecting defects of a photo-thermal fusion imaging device based on heat flow diffusion tracking, which specifically comprises the following steps:
step one: defining a test piece to be detected, and placing the test piece on a two-dimensional mobile station;
step two: starting a defect accurate detection photo-thermal fusion imaging device based on heat flow diffusion tracking; in the second step, the computer, the laser power supply, the data acquisition card, the function generator and the lock-in amplifier are started.
Step three: after the laser power supply is turned on for a plurality of minutes, the laser, the air cooling refrigerator and the semiconductor refrigerator already control the temperature of the laser to be at a preset temperature, and the laser is turned on at the moment; in the third step, the laser power is turned on for 2 minutes, and the laser temperature is controlled at 15 ℃.
Step four: starting the thermal infrared imager and the optical camera, imaging the test sample in real time, irradiating the test sample by using the laser, controlling the motion controller by the computer, and further adjusting the two-dimensional moving table to ensure that the laser beam irradiation positions are all in the fields of view of the thermal infrared imager and the optical camera; in the fourth step, the polarization direction of the polaroid arranged at the front end of the laser is consistent with that of the polaroid in front of the thermal infrared imager, so that effective filtering of signals is realized, the engineering diffuser arranged at the front end of the laser converts a Gaussian light source into uniform light, and meanwhile, the cylindrical lens converts the uniform light source into a linear laser light source.
Step five: the computer controls the function generator to generate a pulse trigger signal, one path of the pulse trigger signal controls the laser to generate constant pulse laser with fixed power, the other path of the pulse trigger signal controls the infrared thermal imager to acquire a thermal radiation image of a test piece according to fixed frequency, meanwhile, the computer controls the two-dimensional moving table and the optical camera to work, the moving direction of the two-dimensional moving table is perpendicular to the direction of the line laser, the positions of the infrared thermal imager, the laser and the optical camera are relatively static, the test piece moves at a uniform speed along with a certain direction of the two-dimensional moving table, the position of the line scanning laser acting on a test field is fixed, and image sequence reconstruction is carried out after scanning is completed as shown in fig. 1;
in the fifth step, a Δpixel_x column Pixel perpendicular to the moving direction of the line-of-view laser heat source is taken, and is defined as the number of collected pixels for reconstruction, and in the scanning process, the Δpixel_x column Pixel will sweep the surface of the detected object along with the heat source and collect and record according to a certain frequency, and in order to enable the Δpixel_x column Pixel to record the heat wave signal of the whole sweeping range, the following relation needs to be satisfied:
wherein v is the moving (scanning) speed of the two-dimensional mobile station, PL is the actual physical position corresponding to a single pixel, and f is the acquisition frequency of the thermal infrared imager;
after the line laser completely scans the tested test piece, the image sequence is reconstructed by using the following formula,
wherein T is seqi The method is characterized in that an ith frame image acquired by a thermal infrared imager is T seq1 1 The reconstructed first image.
Step six: the reconstructed image sequence is equivalent to the thermal image response stimulated by the pulse heat source, and the reconstructed image is subjected to discrete cosine change to obtain the characteristic response image sequence;
in the sixth step, the discrete cosine transform after the image is reconstructed is specifically:
wherein C is u [T seq (t n )]The discrete cosine transform after reconstructing the image, a (u) is an orthogonal transform coefficient, and N is the number of reconstructed image frames.
Step seven: characteristic image sequences of different frequency components can be obtained through discrete cosine transformation, and a corresponding relation curve of phase characteristic differences of the defect position and the defect-free position of the test piece and different frequencies is selected at the moment;
in step seven, the phase characteristic difference is defined as,
DiPH＝|Ph Nondefect {C u [T seq (t n )]}-Ph Defect {C u [T seq (t n )]}| (4)
wherein DipH is the difference in phase characteristics, ph Nondefect Mean value of phase characteristics of defect-free position, ph Defect The phase characteristic mean value of the defect position; selecting the phase characteristic images of the frequencies corresponding to the DipH peak position and the 1/2 position as P respectively peak And P peak/2 。
Step eight: based on two characteristic images, the motion velocity v of the image along the x and y directions is obtained by adopting the method of Rucaskaner x ,v y ；
In step eight, the rate of change in both directions is obtained:
step nine: acquiring a final characteristic image;
the finally acquired characteristic image is as follows:
Ph＝Ph peak/2 -Ph peak ·v x -Ph peak ·v y (6)。
step ten: registering and fusing the acquired characteristic images with the images acquired by the optical camera, and acquiring characteristic values among pixel gaps of the original infrared characteristic images by adopting a fitting method to realize pixel expansion and improvement of image resolution;
step eleven: based on the obtained photo-thermal fusion imaging detection result, performing binarization threshold segmentation and connected domain marking to realize accurate defect detection;
step twelve: after the test is finished, 5 minutes later, the laser power supply, the laser, the function generator, the data acquisition card, the lock-in amplifier, the optical camera and the thermal infrared imager are turned off.
Examples
The computer 20 of the invention is provided with four signal ends, one signal input end of the computer 20 is connected with a signal output end of the thermal infrared imager 1 through a first Ethernet line 4, a second signal input end of the computer 20 is connected with a signal output end of an optical camera 19 through a second Ethernet line 18, a third signal output end of the computer 20 is connected with an input end of the function generator 12 through a first USB communication line 13, a fourth signal output end of the computer 20 is connected with an input end of the motion controller 22 through a second USB communication line 21, one signal input end of the thermal infrared imager 1 is connected with an output end of the function generator 12 through a first BNC control line 2, a second signal output end of the thermal infrared imager 1 is connected with an input end of the optical camera 19 through a second BNC control line 3, the air-cooled refrigerator 6, the semiconductor refrigerator 7 and the laser 8 are mechanically connected through bolts, the output end of the laser 8 is connected with the collimating lens 29 through the conducting optical fiber 5, the cylindrical lens 25, the first polaroid 26, the engineering diffuser 27, the sleeve 28 and the collimating lens 29 are connected on the sleeve 28 through threads, the signal output end of the laser power supply 10 is connected with the input end of the laser 8 through the control line 9, the signal input end of the laser power supply 10 is connected with the signal output end of the function generator 12 through the third BNC control line 11, the signal output end of the function generator 12 is connected with the signal input end of the lock-in amplifier 15 through the fourth BNC control line 14, the output end of the data acquisition card 17 is connected with the signal input end of the lock-in amplifier 15 through the fifth BNC control line 16, the output end of the motion controller 22 is connected with the signal input end of the two-dimensional moving table 24 through the motion control line 23, the clamp 30 is fixed on the two-dimensional moving table 24 through threads, the clamp 30 is used for clamping a test piece 31, and the second polaroid 32 is connected with the thermal infrared imager 1 through threaded connection.
According to the precise defect detection photo-thermal fusion imaging device based on heat flow diffusion tracking shown in fig. 2, in the embodiment, the thermal infrared imager 1 is of the model of FLIR SC6520, the response wavelength is 3.6-5.2 μm, the pixel size is 320×256, the maximum frame frequency is 100Hz, the optical camera pixel is 1920×1080 pixels, and the test piece 31 is a carbon fiber composite material with a prefabricated flat bottom hole for simulating a debonding defect.
The invention provides an imaging method for precisely detecting defects of a photo-thermal fusion imaging device based on heat flow diffusion tracking, which specifically comprises the following steps:
step one: defining a test piece 31 to be detected, and placing the test piece 31 on a two-dimensional mobile station;
step two: starting a defect accurate detection photo-thermal fusion imaging device based on heat flow diffusion tracking, wherein the method comprises the steps of starting a computer 20, a laser power supply 10, a data acquisition card 17, a function generator 12, a lock-in amplifier 15 and other devices;
step three: after the laser power supply 10 is turned on for about 2 minutes, the laser air-cooled refrigerator 6 and the semiconductor refrigerator 7 have controlled the temperature of the laser 8 to 15 ℃, and at this time, the laser 8 is turned on;
step four: the thermal infrared imager 1 and the optical camera 19 are started, real-time imaging is carried out on a test sample, the laser 8 is adopted to irradiate the test sample, the computer 20 controls the motion controller 22, the two-dimensional moving table 24 is further adjusted to ensure that the laser beam irradiation positions are all in the visual field of the thermal infrared imager 1 and the optical camera 19, the polarization direction of the polarization plate 26 arranged at the front end of the laser is consistent with that of the polarization plate 32 arranged in front of the thermal infrared imager 1, effective filtering of signals is achieved, the Gaussian light source is converted into uniform light by the engineering diffuser 27 arranged at the front end of the laser, and meanwhile, the uniform light source is converted into a linear laser light source by the cylindrical lens 25.
Step five: the computer 20 controls the function generator 12 to generate a pulse trigger signal, one path of the pulse trigger signal controls the laser 8 to generate constant pulse laser with fixed power, the other path of the pulse trigger signal controls the thermal imaging system 1 to acquire thermal radiation images of the test piece 31 according to fixed frequency, meanwhile, the computer 20 controls the two-dimensional moving table 24 and the optical camera 19 to work, wherein the moving direction of the two-dimensional moving table 24 is vertical to the line laser direction, the positions of the thermal imaging system 1, the laser 8 and the optical camera 19 are relatively static, the test piece 31 moves at a constant speed along with a certain direction of the two-dimensional moving table 24, and the position of the line scanning laser acting on a test field is fixed.
Taking the delta pixel_x column Pixel of the line-of-view laser heat source perpendicular to the moving direction of the line-of-view laser heat source, defining the Pixel as the collection Pixel number for reconstruction, wherein the delta pixel_x column Pixel can sweep the surface of a detected object along with the heat source in the scanning process and collect and record according to a certain frequency, and the following relational expression needs to be satisfied in order to enable the delta pixel_x column Pixel to record the heat wave signal of the whole sweeping range:
where v is the moving (scanning) speed of the two-dimensional mobile station, PL is the actual physical position corresponding to a single pixel, and f is the acquisition frequency of the thermal infrared imager.
After the line laser completely scans the tested test piece, the image sequence is reconstructed by using the following formula,
wherein T is seqi For the ith frame image acquired by the thermal infrared imager 1, T seq1 1 The reconstructed first image.
Step six: the reconstructed image sequence is equivalent to the thermal image response after being excited by the pulse heat source, the reconstructed image is utilized to obtain the characteristic response image sequence by discrete cosine change,
wherein C is u [T seq (t n )]The discrete cosine transform after reconstructing the image, a (u) is an orthogonal transform coefficient, and N is the number of reconstructed image frames.
Step seven: characteristic image sequences of different frequency components can be obtained through discrete cosine transformation, at the moment, phase characteristic differences of the defect position and the defect-free position of the test piece are selected to correspond to curves of different frequencies, wherein the phase characteristic differences are defined as,
DiPH＝|Ph Nondefect {C u [T seq (t n )]}-Ph Defect {C u [T seq (t n )]}| (10)
wherein DipH is the difference in phase characteristics, ph Nondefect Mean value of phase characteristics of defect-free position, ph Defect Is the defect position phase characteristic mean value. Selecting the phase characteristic images of the frequencies corresponding to the DipH peak position and the 1/2 position as P respectively peak And P peak/2 。
Step eight: based on two characteristic images, the motion velocity v of the image along the x and y directions is obtained by adopting the method of Rucaskaner x ,v y Wherein, the method can describe the transformation process of two characteristic images, thereby obtaining the change rates of two directions,
step nine: the characteristic image which is finally acquired is that,
Ph＝Ph peak/2 -Ph peak ·v x -Ph peak ·v y (12)
step ten: and registering and fusing the acquired characteristic image with the image acquired by the optical camera 19, and acquiring the characteristic value between the pixel gaps of the original infrared characteristic image by adopting a fitting method to realize pixel expansion and image resolution improvement.
Step eleven: and performing binarization threshold segmentation and connected domain marking based on the obtained photo-thermal fusion imaging detection result to realize accurate defect detection.
Step twelve: after the test is finished, 5 minutes after the test is finished, the laser power supply 10, the laser 8, the function generator 12, the data acquisition card 17, the lock-in amplifier 15, the optical camera 19, the thermal infrared imager 1 and other devices are turned off.
The test results for the test piece are shown in fig. 3, in which the error of detection is less than 2% for the three simulated flat bottom hole defect diameters.
The invention provides a defect accurate detection photo-thermal fusion imaging device and method based on heat flow diffusion tracking, which are described in detail, wherein specific examples are applied to illustrate the principle and implementation of the invention, and the description of the above examples is only used for helping to understand the method and core ideas of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (3)
1. The imaging method of the defect detection photo-thermal fusion imaging device based on heat flow diffusion tracking is characterized in that the imaging device comprises a thermal infrared imager, a first BNC control line, a second BNC control line, a first Ethernet line, a conducting optical fiber, an air-cooled refrigerator, a semiconductor refrigerator, a laser, a control line, a laser power supply, a third BNC control line, a function generator, a first USB communication line, a fourth BNC control line, a lock-in amplifier, a fifth BNC control line, a data acquisition card, a second Ethernet line, an optical camera, a computer, a second USB communication line, a motion controller, a motion control line, a two-dimensional mobile station, a cylindrical lens, a first polarizer, an engineering diffuser, a sleeve, a collimating mirror, a clamp, a test piece and a second polarizer;
the computer is provided with four signal ends, one signal input end of the computer is connected with the signal output end of the thermal infrared imager through a first Ethernet wire, the second signal input end of the computer is connected with the signal output end of the optical camera through a second Ethernet wire, the third signal output end of the computer is connected with the input end of the function generator through a first USB communication wire, the fourth signal output end of the computer is connected with the input end of the motion controller through a second USB communication wire, one signal input end of the thermal infrared imager is connected with the output end of the function generator through a first BNC control wire, the second signal output end of the thermal infrared imager is connected with the input end of the data acquisition card through a second BNC control wire, the air cooling refrigerator, the semiconductor refrigerator and the laser are mechanically connected with the collimating mirror through a conducting optical fiber, the cylindrical lens, the first polarizer, the engineering body and the collimating mirror are connected on the sleeve through threads, the signal output end of the laser power supply is connected with the input end of the laser through a control wire, the signal output end of the laser power supply is connected with the input end of the laser through a second USB communication wire, the signal output end of the thermal infrared imager is connected with the output end of the laser through a second BNC control wire, the signal output end of the thermal infrared imager is connected with the output end of the optical fiber through a second BNC control wire, the optical fiber is connected with the output end of the optical fiber through a two-dimensional amplifier, and the optical fiber is connected with the output end of the optical fiber through the optical fiber;
the imaging method specifically comprises the following steps:
step one: defining a test piece to be detected, and placing the test piece on a two-dimensional mobile station;
step two: starting a defect detection photo-thermal fusion imaging device based on heat flow diffusion tracking;
step three: after the laser power supply is turned on for a plurality of minutes, the laser, the air cooling refrigerator and the semiconductor refrigerator already control the temperature of the laser to be at a preset temperature, and the laser is turned on at the moment;
step four: starting the thermal infrared imager and the optical camera, imaging a test piece to be detected in real time, irradiating the test piece by adopting a laser, controlling the motion controller by a computer, and further adjusting the two-dimensional moving table to ensure that the irradiation positions of the laser beams are all in the fields of view of the thermal infrared imager and the optical camera;
step five: the computer controls the function generator to generate a pulse trigger signal, one path of the pulse trigger signal controls the laser to generate constant pulse laser with fixed power, the other path of the pulse trigger signal controls the infrared thermal imager to acquire a thermal radiation image of the test piece according to fixed frequency, meanwhile, the computer controls the two-dimensional moving table and the optical camera to work, the moving direction of the two-dimensional moving table is perpendicular to the direction of the line laser, the positions of the infrared thermal imager, the laser and the optical camera are relatively static, the test piece moves at a uniform speed along with a certain direction of the two-dimensional moving table, the position of the line scanning laser acting on a visual field is fixed, and image sequence reconstruction is carried out after scanning is completed;
step six: the reconstructed image sequence is equivalent to the thermal image response stimulated by the pulse heat source, and the reconstructed image is subjected to discrete cosine change to obtain the characteristic response image sequence;
step seven: characteristic response image sequences of different frequency components can be obtained through discrete cosine transformation, and a corresponding relation curve of phase characteristic differences of the defect position and the defect-free position of the test piece and different frequencies is selected at the moment;
step eight: based on the two characteristic response images, the motion velocity v of the image along the x and y directions is obtained by adopting the method of Rucaskaner x ,v y ；
Step nine: acquiring a final characteristic response image;
step ten: registering and fusing the acquired characteristic response image and the image acquired by the optical camera, and acquiring a characteristic value between pixel gaps of the original infrared characteristic image by adopting a fitting method;
step eleven: based on the obtained photo-thermal fusion imaging detection result, performing binarization threshold segmentation and connected domain marking to realize defect detection;
step twelve: after the test is finished, 5 minutes later, the power supply of the laser, the function generator, the data acquisition card, the lock-in amplifier, the optical camera and the thermal infrared imager are turned off;
in the fourth step, the polarization direction of a polaroid arranged at the front end of the laser is consistent with that of a polaroid in front of the thermal infrared imager, so that effective filtering of signals is realized, an engineering diffuser arranged at the front end of the laser converts a Gaussian light source into uniform light, and a cylindrical lens converts the uniform light source into a linear laser light source;
in step five, the DeltaPixel x column pixels, which are perpendicular to the movement direction of the laser heat source in the line of view, are defined as being used for
The number of reconstructed acquisition pixels, the Δpixel_x column pixels sweep the surface of the detected object along with the heat source in the scanning process and acquire and record according to a certain frequency, and in order to enable the Δpixel_x column pixels to record the heat wave signals of the whole sweeping range, the following relational expression needs to be satisfied:
wherein v is the moving speed of the two-dimensional mobile station, PL is the actual physical position corresponding to a single pixel, and f is the acquisition frequency of the thermal infrared imager;
after the line laser completely scans the tested test piece, the image sequence is reconstructed by using the following formula,
wherein T is seqi The method is characterized in that an ith frame image acquired by a thermal infrared imager is T seq1 1 A reconstructed first image;
in the sixth step, the discrete cosine transform after the image is reconstructed is specifically:
wherein C is u [T seq (t n )]Discrete cosine transform after reconstructing an image, a (u) is an orthogonal transform coefficient, and N is the number of frames of the reconstructed image;
in step seven, the phase characteristic difference is defined as,
DiPH＝|Ph Nondefect {C u [T seq (t n )]}-Ph Defect {C u [T seq (t n )]}| (4)
wherein DipH is the difference in phase characteristics, ph Nondefect Mean value of phase characteristics of defect-free position, ph Defect The phase characteristic mean value of the defect position; selecting the phase characteristic response images of the frequencies corresponding to the DipH peak position and the 1/2 position as P respectively peak And P peak/2 ；
In step eight, the rate of change in both directions is obtained:
the finally obtained characteristic response image is as follows:
Ph＝Ph peak/2 -Ph peak ·v x -Ph peak ·v y (6)。
2. the imaging method of claim 1, wherein in step two, the computer, the laser power supply, the data acquisition card, the function generator, and the lock-in amplifier are turned on.
3. The imaging method of claim 2, wherein in step three, the laser is powered on for 2 minutes and the laser temperature is controlled at 15 ℃.
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